Hard Conversations: Navigating Cases of Suspected AI Misuse

As we approach the end of the semester, one topic on many faculty members’ minds is undisclosed AI use. Whether you prohibit AI use entirely or place just a few limitations, you know that restricting AI use is easier said than done. Students may misuse AI in a number of ways that result in academic integrity violations, including using AI in ways prohibited by course policies or assignment directions; failing to adequately attribute their AI use; or using AI in ways that produce other academic integrity violations, such as misrepresentations of sources or fabricated citations. So what should you do as an instructor if you’re reading a paper and suspect AI misuse?

Determining if AI Misuse Occurred

When you suspect a violation of your AI policy or other course policies, the question you need to answer is whether it is “more likely than not” that the student engaged in misconduct. This “preponderance of evidence” standard is the one outlined in University policy and used by entities like the Office of Community Standards. Misconduct does not need to be proven beyond a reasonable doubt.

Signs of possible AI misuse can include nonexistent, fabricated, or misinterpreted sources; lack of connection to class content and discussions; inclusion of high-level material not covered in your course; or major differences in voice or level of sophistication from students’ prior work. 

Keep in mind, however, that many features sometimes cited as hallmarks of AI writing actually have multiple possible causes. For example, students grappling with a new concept may produce papers that make overbroad claims or summarize without deeply analyzing or synthesizing. Unintentional misrepresentation of sources may result from reading comprehension challenges or confusion among sources. A student might be taking other courses with overlapping content or reading independently, leading to different framing of a concept than you presented in class. Linguistic features like em-dashes or “not just X, but Y” phrasing appear frequently in AI text precisely because they are fixtures of academic writing. And students using a thesaurus tool too liberally may end up with confusing language choices that read like the output of a text spinner. These distinctions become doubly complex if you allow some kinds of AI use, e.g. for translation or grammar correction. In short, textual features may suggest AI (mis)use, but in isolation, they are rarely sufficient proof of academic misconduct. Instead, it’s time to start digging deeper. 

Avoid AI Detectors

Generally, AI detectors aren’t great options for determining whether AI misuse has occurred, as outlined by UMN Teaching Support. AI detectors have low accuracy (e.g., Hadra et al., 2026), particularly when students blend their own language and AI text (Hadra et al., 2026), and are particularly biased against multilingual English users (e.g., Lege, 2025) and neurodiverse people (e.g., Eaton, 2025). Moreover, uploading students’ work to an unapproved tool with unknown security is a FERPA violation, since it shares student educational information with outside parties. For these reasons, we recommend skipping AI detectors.

Talk to Students!

The easiest way to learn more in cases of suspected AI misuse is to talk with students about it! You can often learn a great deal just by asking students to share more about their experiences with the assignment. Consider posing questions like these and documenting the student’s responses:

• Tell me about your writing/research process for this assignment.
• What drafts or notes did you create when writing this paper?
• What was your favorite part of this paper to write? What parts of the assignment were most challenging?
• What made you decide to write about this topic/argue this position? How did you come up with these ideas?
• How did your thinking shift as you read sources? As you wrote your paper?
• Which aspect of your argument or piece of evidence do you think is most compelling?
• Can you summarize your argument for me? How would you explain it to someone unfamiliar with the topic?
• You brought up [a particular theory or term we didn’t discuss in class]. Can you explain it to me? How did you learn about it? Why did you opt to use it in this paper?
• Why did you decide to structure the paper the way you did? What alternatives did you consider?
• How did you find your sources? What sources did you consider, but decide not to include? Do you have any notes or annotations on the sources you read?
• What was the most useful source you found? Tell me about it.
• This sounds very different from some of your other work to me. What do you think? Why might that be?
• Did you use any generative AI tools, like ChatGPT or Grammarly? How did you use them?
• Did you use any translation tools like Google Translate? How did you use them?

Remember that some students, particularly multilingual students and neurodiverse students, may be more able to articulate their ideas in writing than in speaking. You shouldn’t expect that students can perfectly recreate their arguments or ideas verbally, especially without referencing their text. However, students with almost no knowledge of a portion of their text, or who can’t describe their writing process, likely over-relied on some external source, such as an AI tool.

In some courses, TAs and graders read most of the writing students produce and have more opportunities to interact with students in small group settings. This positions them well to notice changes in students’ writing that may be markers of over-reliance on or misuse of AI. While instructors of record need to be involved in decisions to assign penalties for academic misconduct, TAs can absolutely be responsible for having conversations with students about suspected AI use, making this strategy much more feasible in large courses. The instructor of record should give TAs some guidance on navigating the conversation and remind them to carefully document the student’s responses.

Of course, opening a conversation with students about their writing isn’t just helpful in illuminating AI misuse. It also allows broader discussions of students’ writing process, surfaces possible misconceptions (e.g. “I just used Grammarly, not AI”), and provides an opportunity to clarify your expectations.

Identifying an Appropriate Penalty

If you determine that it is more likely than not that academic misconduct occurred, your next step is to determine an appropriate penalty. Consequences can range from requiring the student to redo the assignment, to reduced or no credit for the assignment, to a lowered or failing grade in the course. The Office of Community Standards provides this guidance for instructors on selecting an appropriate academic penalty.

Follow OCS Procedures

When you assign a penalty, be sure to report the suspected misconduct and the penalty you chose to the Office of Community Standards (on the Twin Cities campus) or other campus entity dictated by policy (for other UMN campuses). Reporting suspected academic dishonesty to the Office of Community Standards provides students with due process, including formal notification of penalties and the opportunity to schedule a hearing to contest the accusations. For this reason, University policy dictates that, in any instance where there is a consequence for academic dishonesty, it must be reported. You can learn more about the Student Conduct Process here.

TAs can also be involved in reporting academic misconduct. Office of Community Standards Director Lauren Adamski confirmed that, with approval from the instructor of record, TAs can take the lead on filing reports in cases of suspected academic misconduct—in fact, this is preferable in cases where TAs have the most first-hand knowledge of the academic misconduct. Involving TAs in the reporting process reduces burdens on the instructor, enables TAs to share evidence they encountered, and helps prepare them to teach courses independently in the future.

Take Notes for Next Time

High rates of suspected AI misuse are undoubtedly frustrating, but they are also useful data for you about the ways students are responding to your policies and assignments. As you wrap up this semester’s assignments, take notes about when and where you observe students over-relying on AI tools. Then, come back for Part 2 in fall to learn more about strategies for reducing AI misuse. (If you don’t already receive it, subscribe to the WAC Update to be notified!) In the meantime, you can consult with a member of the WAC team to discuss specifics of your assignment. And please share your strategies below: How do you approach conversations with students about AI misuse? How do you discourage AI misuse in your courses?

Thanks to Lauren Adamski, Matt Luskey, and Katie Levin for input on this blog post!